HypoTestResult.h

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// @(#)root/roostats:$Id$
// Author: Kyle Cranmer, Lorenzo Moneta, Gregory Schott, Wouter Verkerke, Sven Kreiss
/*************************************************************************
 * Copyright (C) 1995-2008, Rene Brun and Fons Rademakers.               *
 * All rights reserved.                                                  *
 *                                                                       *
 * For the licensing terms see $ROOTSYS/LICENSE.                         *
 * For the list of contributors see $ROOTSYS/README/CREDITS.             *
 *************************************************************************/
#ifndef ROOSTATS_HypoTestResult
#define ROOSTATS_HypoTestResult
 
#include "RooStats/RooStatsUtils.h"
#include "RooStats/SamplingDistribution.h"
 
#include "TNamed.h"
 
#include <memory>
 
namespace RooStats {
 
   class HypoTestResult : public TNamed {
 
   public:
 
      /// default constructor
      explicit HypoTestResult(const char* name = 0);
 
      /// copy constructor
      HypoTestResult(const HypoTestResult& other);
 
      /// constructor from name, null and alternate p values
      HypoTestResult(const char* name, Double_t nullp, Double_t altp);
 
      /// destructor
      virtual ~HypoTestResult();
 
      /// assignment operator
      HypoTestResult & operator=(const HypoTestResult& other);
 
      /// add values from another HypoTestResult
      virtual void Append(const HypoTestResult *other);
 
      /// Return p-value for null hypothesis
      virtual Double_t NullPValue() const { return fNullPValue; }
 
      /// Return p-value for alternate hypothesis
      virtual Double_t AlternatePValue() const { return fAlternatePValue; }
 
      /// Convert  NullPValue into a "confidence level"
      virtual Double_t CLb() const { return !fBackgroundIsAlt ? NullPValue() : AlternatePValue(); }
 
      /// Convert  AlternatePValue into a "confidence level"
      virtual Double_t CLsplusb() const { return !fBackgroundIsAlt ? AlternatePValue() : NullPValue(); }
 
      /// \f$CL_{s}\f$ is simply \f$CL_{s+b}/CL_{b}\f$ (not a method, but a quantity)
      virtual Double_t CLs() const {
         double thisCLb = CLb();
         if (thisCLb == 0) {
            std::cout << "Error: Cannot compute CLs because CLb = 0. Returning CLs = -1\n";
            return -1;
         }
         double thisCLsb = CLsplusb();
         return thisCLsb / thisCLb;
      }
 
      /// familiar name for the Null p-value in terms of 1-sided Gaussian significance
      virtual Double_t Significance() const {return RooStats::PValueToSignificance( NullPValue() ); }
 
      SamplingDistribution* GetNullDistribution(void) const { return fNullDistr; }
      SamplingDistribution* GetAltDistribution(void) const { return fAltDistr; }
      RooDataSet* GetNullDetailedOutput(void) const { return fNullDetailedOutput; }
      RooDataSet* GetAltDetailedOutput(void) const { return fAltDetailedOutput; }
      RooDataSet* GetFitInfo() const { return fFitInfo.get(); }
      Double_t GetTestStatisticData(void) const { return fTestStatisticData; }
      const RooArgList* GetAllTestStatisticsData(void) const { return fAllTestStatisticsData; }
      Bool_t HasTestStatisticData(void) const;
 
      void SetAltDistribution(SamplingDistribution *alt);
      void SetNullDistribution(SamplingDistribution *null);
      void SetAltDetailedOutput(RooDataSet* d) { fAltDetailedOutput = d; }
      void SetNullDetailedOutput(RooDataSet* d) { fNullDetailedOutput = d; }
      void SetFitInfo(RooDataSet* d) { fFitInfo.reset(d); }
      void SetTestStatisticData(const Double_t tsd);
      void SetAllTestStatisticsData(const RooArgList* tsd);
 
      void SetPValueIsRightTail(Bool_t pr);
      Bool_t GetPValueIsRightTail(void) const { return fPValueIsRightTail; }
 
      void SetBackgroundAsAlt(Bool_t l = kTRUE) { fBackgroundIsAlt = l; }
      Bool_t GetBackGroundIsAlt(void) const { return fBackgroundIsAlt; }
 
      /// The error on the "confidence level" of the null hypothesis
      Double_t CLbError() const;
 
      /// The error on the "confidence level" of the alternative hypothesis
      Double_t CLsplusbError() const;
 
      /// The error on the ratio \f$CL_{s+b}/CL_{b}\f$
      Double_t CLsError() const;
 
      /// The error on the Null p-value
      Double_t NullPValueError() const;
 
      /// The error on the significance, computed from NullPValueError via error propagation
      Double_t SignificanceError() const;
 
 
      void Print(const Option_t* = "") const;
 
   private:
      void UpdatePValue(const SamplingDistribution* distr, Double_t &pvalue, Double_t &perror,  Bool_t pIsRightTail);
 
 
   protected:
 
      mutable Double_t fNullPValue; // p-value for the null hypothesis (small number means disfavoured)
      mutable Double_t fAlternatePValue; // p-value for the alternate hypothesis (small number means disfavoured)
      mutable Double_t fNullPValueError; // error of p-value for the null hypothesis (small number means disfavoured)
      mutable Double_t fAlternatePValueError; // error of p-value for the alternate hypothesis (small number means disfavoured)
      Double_t fTestStatisticData; // result of the test statistic evaluated on data
      const RooArgList* fAllTestStatisticsData; // for the case of multiple test statistics, holds all the results
      SamplingDistribution *fNullDistr;
      SamplingDistribution *fAltDistr;
      RooDataSet* fNullDetailedOutput;
      RooDataSet* fAltDetailedOutput;
      std::unique_ptr<RooDataSet> fFitInfo;
      Bool_t fPValueIsRightTail;
      Bool_t fBackgroundIsAlt;
 
      ClassDef(HypoTestResult,4)  // Base class to represent results of a hypothesis test
 
   };
}
 
 
#endif